Adapting Operator Settings in Genetic Algorithms

Abstract

In the majority of genetic algorithm implementations, the operator settings are fixed throughout a given run. However, it has been argued that these settings should vary over the course of a genetic algorithm run--so as to account for changes in the ability of the operators to produce children of increased fitness. This paper describes an investigation into… (More)